fabric-data-cleaner Skill

Source

• Creator: microsoft
• Repository: microsoft/gh-copilot-fabric-agents
• Skill file: .github/skills/fabric-data-cleaner/SKILL.md

What it does

Algorithm reference and self-contained PySpark notebook templates for cleaning Microsoft Fabric lakehouse tables. Covers profiling, duplicate detection, null analysis, type validation, statistics, IQR outlier detection, date format validation, Spanish DNI/NIE checksum validation, and email/phone format checks. Each not

Skill instructions

Fabric Data Cleaner — Algorithm Reference Self-contained PySpark .ipynb notebook templates for cleaning Microsoft Fabric lakehouse tables. Each notebook can be uploaded and run independently — configure {{TABLENAME}} and {{LAKEHOUSENAME}} in the first cell, run all cells to analyze, then optionally run the fix cell. Column Classification Rules Classify the table's columns to select which notebooks to use: | Category | Detection Rule | Which Notebook | |----------|---------------|----------------| | Numeric | Type is int, long, float, double, decimal | typevalidation.ipynb, statistics.ipynb, outliers.ipynb | | Date/Timestamp | Type is date or timestamp, or column name contains date, fecha, time | datevalidation.ipynb | | DNI/Personal ID | Column name contains dni, nie, nif, documento, identidad, idpersonal | dnivalidation.ipynb | | Email | Column name contains email, correo, mail | contactvalidation.ipynb | | Phone | Column name contains phone, tel, movil, telefono | contactvalidation.i